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Purpose <p>Prediction of major complications (mPOC) after major digestive surgery (MDS) remains challenging. Perioperative gain of weight (ΔWeight) was identified as a promising marker of morbidity after specific types of surgery. This study aimed to assess the predictive value of ΔWeight for mPOC after MDS.</p> Methods <p>Retrospective analysis of consecutive patients undergoing MDS between 2013 and 2022. MDS was defined as elective surgery with anticipated duration of ≥ 120&#xa0;min. Test variable was postoperative weight change calculated on postoperative day 2, defined as ΔWeight. Complications were graded according to Clavien classification. Primary outcome was mPOC (grades &gt; II). Secondary outcomes were overall complications, Comprehensive Complication Index (CCI) and specific subtypes of complications.</p> Results <p>A total of 1402 patients were included. MPOC were reported in 392 (27.9%). Median ΔWeight was 2.0&#xa0;kg [0.4–3.8]. Area under the curve (AUC) of ΔWeight for mPOC was 0.614 (<i>p</i> &lt; 0.001) and maximal Youden index determined a cut-off of 2.6&#xa0;kg, yielding a negative predictive value of 79%. Patients with ΔWeight above this cut-off showed higher rates of mPOC (38.2 vs. 20.7%, <i>p</i> &lt; 0.001), overall complications (76.2 vs. 47.2%, <i>p</i> &lt; 0.001), anastomotic leak (9.2 vs. 5.0%, <i>p</i> = 0.002), and higher CCI (33.7 vs. 29.6, <i>p</i> &lt; 0.001). Multivariable analysis identified ΔWeight ≥ 2.6&#xa0;kg as an independent predictor of mPOC (OR, 1.49; 95% CI, 1.03–2.16; <i>p</i> = 0.033).</p> Conclusion <p>ΔWeight emerged as a risk-stratification marker across complication types and an independent predictor of major postoperative complications after MDS. This supports perioperative weight monitoring, proactive mitigation of postoperative weight gain, and future studies developing multiparametric prediction tools.</p>

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Perioperative weight gain (ΔWeight): an independent predictor of major complications after major digestive surgery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月30日

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  • Maximilien Ravenel,
  • Asaad Khadda,
  • Emilie Zhu,
  • Laura Didisheim,
  • Gaëtan-Romain Joliat,
  • Stéphanie Gonvers,
  • David Fuks,
  • Fabian Grass,
  • Dieter Hahnloser,
  • Martin Hübner,
  • Styliani Mantziari,
  • Emmanuel Melloul,
  • Markus Schäfer,
  • Hugo Teixeira,
  • Emilie Uldry,
  • Ismail Labgaa

摘要

Purpose

Prediction of major complications (mPOC) after major digestive surgery (MDS) remains challenging. Perioperative gain of weight (ΔWeight) was identified as a promising marker of morbidity after specific types of surgery. This study aimed to assess the predictive value of ΔWeight for mPOC after MDS.

Methods

Retrospective analysis of consecutive patients undergoing MDS between 2013 and 2022. MDS was defined as elective surgery with anticipated duration of ≥ 120 min. Test variable was postoperative weight change calculated on postoperative day 2, defined as ΔWeight. Complications were graded according to Clavien classification. Primary outcome was mPOC (grades > II). Secondary outcomes were overall complications, Comprehensive Complication Index (CCI) and specific subtypes of complications.

Results

A total of 1402 patients were included. MPOC were reported in 392 (27.9%). Median ΔWeight was 2.0 kg [0.4–3.8]. Area under the curve (AUC) of ΔWeight for mPOC was 0.614 (p < 0.001) and maximal Youden index determined a cut-off of 2.6 kg, yielding a negative predictive value of 79%. Patients with ΔWeight above this cut-off showed higher rates of mPOC (38.2 vs. 20.7%, p < 0.001), overall complications (76.2 vs. 47.2%, p < 0.001), anastomotic leak (9.2 vs. 5.0%, p = 0.002), and higher CCI (33.7 vs. 29.6, p < 0.001). Multivariable analysis identified ΔWeight ≥ 2.6 kg as an independent predictor of mPOC (OR, 1.49; 95% CI, 1.03–2.16; p = 0.033).

Conclusion

ΔWeight emerged as a risk-stratification marker across complication types and an independent predictor of major postoperative complications after MDS. This supports perioperative weight monitoring, proactive mitigation of postoperative weight gain, and future studies developing multiparametric prediction tools.